In recent years, many businesses have identified post-sales service as an important driver of revenue and profitable growth. Post-sales revenue accounts for a significant portion of the total revenue stream of many companies. For example, after a piece of hardware, like a printer, is sold, significant revenue is generated in post-sales service of that hardware. As such, it has become increasingly important to devise efficient and cost effective methods and systems for providing post-sale service.
In order to reduce machine service hours and related service costs, remote service tools have been developed. Such remote service tools include on machine diagnostics and Eureka tips used by customer service engineers to service malfunctioning hardware. However, these and other similar tools have limited value in aiding service calls received by a technical support center. A review of such calls suggests only 40% can be resolved using these tools.
Additionally, most technical service companies maintain databases that track service data in a variety of ways. However, this data is often noisy, incomplete, or conflicting and therefore of little practical value. This is a result of the data being collected from different sources and by different means. Analyzing this data is difficult because it is difficult to confidently provide users with accurate results.
A classical or Bayesian probabilistic approach to combining information is not suitable for this problem. For example, the additivity principle of probability requires that the probability of mutually disjoint elements in a state space must add to one. This makes it cumbersome to express ignorance as a scalar probability value. For example, assume that a service call could have been caused by one of five different problems, but that nothing else is known about the situation. Then the statement “I don't know the cause of the service call” is translated in the classical probabilistic framework as “All five causes of the service call are equally likely”. Such an approach provides an implicit expression of uncertainty or ignorance. This can be awkward to implement as it requires that a probability be assigned to every element of the state space.
Therefore, there is a need in the art for an improved method of utilizing a variety of data sources to develop accurate service rules and thereby reduce after sales service costs.